MétaCan
Menu
Back to cohort
Record W2094911678 · doi:10.1021/ie000846b

Surface Analysis of Ground Calcium Carbonate Filler Treated with Dissolution Inhibitor

2001· article· en· W2094911678 on OpenAlexaff
Peter K.T. Pang, Yves Deslandes, S. Raymond, G. Pleizier, Peter Englezos

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2001
Typearticle
Languageen
FieldEngineering
TopicBone Tissue Engineering Materials
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDissolutionX-ray photoelectron spectroscopyCalcium carbonateSolubilityPhosphateScanning electron microscopePrecipitationTransmission electron microscopyCalciumChemistryCarbonateChemical engineeringNuclear chemistryMineralogyMaterials scienceOrganic chemistryNanotechnologyComposite material

Abstract

fetched live from OpenAlex

This work demonstrates that the solubility of ground calcium carbonate (GCC) decreased when GCC was treated with phosphate-containing chemical inhibitors. The extent of inhibition of the dissolution process was found to increase with inhibitor dosage until a saturation point was reached, beyond which further addition of inhibitor did not have any further effect. The mechanism of the inhibition was investigated by conducting surface analysis of the treated GCC. X-ray photoelectron spectroscopy, X-ray diffraction, transmission electron microscopy, and energy-dispersive X-ray analysis were employed to confirm the presence of phosphate on the surface of the treated GCC. Scanning electron microscopic pictures revealed that the treated GCC particles had a different surface morphological pattern than the untreated GCC particles. It is proposed that the inhibition was brought about by the precipitation of calcium phosphate phases such as hydroxyapatite on the GCC surface.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.069
GPT teacher head0.300
Teacher spread0.231 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations16
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueIndustrial & Engineering Chemistry ResearchSame topicBone Tissue Engineering MaterialsFrench-language works237,207